Jon Crowcroft

Bio: Jon Crowcroft is an academic researcher from University of Cambridge. The author has contributed to research in topics: The Internet & Multicast. The author has an hindex of 87, co-authored 672 publications receiving 38848 citations. Previous affiliations of Jon Crowcroft include Memorial University of Newfoundland & Information Technology University.

Smart Signage: An Interactive Signage System with Multiple Displays

Abstract: Digital signs (e.g. electronic billboards), as the replacement of traditional static signs (e.g. paper posters), have gained increasing popularity, especially for out-of-home advertising. The pervasiveness of the smartphones makes it possible to implement new interactive signage systems for advertising purpose. A new drag gable cyber-physical broadcast/multicast media system, Smart Signage, is proposed in our previous work. It allows multiples users simultaneously obtaining the displayed content with an intuitive ``dragging" hand gesture. With the increasing number of deployed digital signs, it is possible that there are multiple signs in one location. In this paper, a new approach is proposed using the existing Smart Signage infrastructure to allow smartphones to interact with multiple digital signs in one location. This approach differentiates signs by the orientations of the signage displays, which are measured by smartphone-embedded orientation sensors. A user can interact with the intended sign by simply pointing his/her smartphone at the target signage display. With this new approach, Smart Signage successfully extends from one-to-many interaction to many-to-many interaction.

Poster: SoftOffload: a programmable approach toward collaborative mobile traffic offloading

Abstract: The fast increase of mobile traffic from smartphone-like devices has created a huge pressure for the cellular operators to manage the network infrastructure and resources. Offloading the mobile traffic to alternative networks such as WiFi is sought as a promising direction to solve this problem cost-effectively. According to our study and experimental findings, existing research proposals are lack of concern for the complexity of network deployment and device limitations, which impedes the solution deployment. To overcome such challenge, we propose SoftOffload, a programmable framework for collaborative mobile traffic offloading. SoftOffload takes the advantage of software defined networking (SDN) paradigm in terms of openness and extensibility. We have implemented the first prototype utilising the open source Floodlight platform.

Data Analytics Service Composition and Deployment on Edge Devices.

Abstract: Data analytics on edge devices has gained rapid growth in research, industry, and different aspects of our daily life. This topic still faces many challenges such as limited computation resource on edge devices. In this paper, we further identify two main challenges: the composition and deployment of data analytics services on edge devices. We present the Zoo system to address these two challenge: on one hand, it provides simple and concise domain-specific language to enable easy and and type-safe composition of different data analytics services; on the other, it utilises multiple deployment backends, including Docker container, JavaScript, and MirageOS, to accommodate the heterogeneous edge deployment environment. We show the expressiveness of Zoo with a use case, and thoroughly compare the performance of different deployment backends in evaluation.

Data Analytics Service Composition and Deployment on IoT Devices

Abstract: Thiswork is funded in part by the EPSRC Databox project (EP/N028260/2), NaaS (EP/K031724/2) and Contrive (EP/N028422/1).

Proactive multi-path routing

Abstract: Internet service provider faces a daunting challenge in provisioning network efficiently. We introduce a proactive multipath routing scheme that tries to route traffic according to its built-in properties. Based on mathematical analysis, our approach disperses incoming traffic flows onto multiple paths according to path qualities. Long-lived flows are detected and migrated to the shortest path if their QoS could be guaranteed there. Suggesting nondisjoint path set, four types of dispersion policies are analyzed, and flow classification policy which relates flow trigger with link state update period is investigated. Simulation experiments show that our approach outperforms traditional single path routing significantly.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Community detection in graphs

Abstract: The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices of the same cluster and comparatively few edges joining vertices of different clusters. Such clusters, or communities, can be considered as fairly independent compartments of a graph, playing a similar role like, e. g., the tissues or the organs in the human body. Detecting communities is of great importance in sociology, biology and computer science, disciplines where systems are often represented as graphs. This problem is very hard and not yet satisfactorily solved, despite the huge effort of a large interdisciplinary community of scientists working on it over the past few years. We will attempt a thorough exposition of the topic, from the definition of the main elements of the problem, to the presentation of most methods developed, with a special focus on techniques designed by statistical physicists, from the discussion of crucial issues like the significance of clustering and how methods should be tested and compared against each other, to the description of applications to real networks.